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Visar resultat 1 - 5 av 41 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Recommender Systems Using Limited Dataset Sizes

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Carl Bentzer; Harry Thulin; [2023]
    Nyckelord :;

    Sammanfattning : In order to create personalized recommendations for users on services such as e-commerce websites and streaming platforms, recommender systems often utilize various machine learning techniques. A common technique used in recommender systems is collaborative filtering which creates rating predictions based on similar users’ interests. LÄS MER

  3. 2. From Data to Decision: : Using Logistic Regression to Determine Creditworthiness

    Kandidat-uppsats, KTH/Matematisk statistik

    Författare :Joel Norling; Sami Abdu; [2023]
    Nyckelord :Bachelor Thesis; Scorecard modeling; Mathematical Statistics; Logistic Regression; Consumer Credits; Binning; Kandidatuppsats; Scorecard-modellering; Matematisk statistik; Logistisk regression; Konsumentkrediter; Binning;

    Sammanfattning : The development of scorecards for customer credit rating is a well-established field in the financial sector. The aim of this project, conducted in collaboration with a Swedish credit institute, was to develop a statistical model for predicting customer performance. LÄS MER

  4. 3. Risk Assessment of Digital Assets – Insurance Applications in Cryptocurrencies and NFTs

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Roberto Delgado Ferrezuelo; [2023]
    Nyckelord :Blockchain; NFTs; private key; phishing; floor price; rarity; cold wallet; hot wallet; risk premium; Technology and Engineering;

    Sammanfattning : The aim of the project is to develop a framework for an insurance policy for digital assets. The project comprised several stages, starting with the identification of risks associated with these assets. Policyholders were then categorized into two groups based on a predefined rating factor. LÄS MER

  5. 4. Predicting Airbnb Prices in European Cities Using Machine Learning

    Kandidat-uppsats, Blekinge Tekniska Högskola/Fakulteten för datavetenskaper

    Författare :Shalini Gangarapu; Venkata Surya Akash Mernedi; [2023]
    Nyckelord :Machine Learning; Supervised Learning; Regression Algorithms; Airbnb Price Prediction;

    Sammanfattning : Background: Machine learning is a field of computer science that focuses on creating models that can predict patterns and relations among data. In this thesis, we use machine learning to predict Airbnb prices in various European cities to help the hosts in setting reasonable prices for their properties. LÄS MER

  7. 5. Investigating Validity of Semantic Measures vs Rating Scales in Assessing Personality

    Kandidat-uppsats, Lunds universitet/Institutionen för psykologi

    Författare :Sofie Gustavsson; Henrietta Plate; [2023]
    Nyckelord :Rating scales; semantic measures; Five Factor Model of personality; The Big Five; IPIP-NEO 30; Natural Language Processing; Social Sciences;

    Sammanfattning : Within personality research, self-report questionnaires are a common approach. This study takes aim at investigating whether self-report questionnaires are enough, or if semantic measures, through Natural Language Processing, could be a substitute or complementary method, in assessing personality. LÄS MER